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English
$
USD
I will build a custom ai agent with rag, mcp and vector database
Badar Younas
About this gig
Need an AI agent that actually does work, not just chat? I build custom, production-ready AI agents that reason, use tools, connect to your systems, and answer from your data.
WHAT I BUILD
- AI agents with tool calling, memory, multi-step workflows, and LLM integration
- RAG chatbots and AI assistants trained on your PDFs, documents, websites, and databases
- Custom MCP servers and MCP integrations that connect AI to APIs, CRMs, and internal tools
- Vector database solutions using ChromaDB, pgvector, or MongoDB Atlas
- AI automation and full-stack AI applications with React, Node.js, and Express
TECH STACK
OpenAI, Gemini, MCP, RAG, LLMs, Node.js, React, Express, MongoDB, ChromaDB, pgvector, Redis, BullMQ, and Socket.io.
WHY WORK WITH ME
-Full-stack MERN + AI developer
-Complete AI agent and application development
-Real-time streaming, Redis caching, and background queue workers
-Clean, scalable, documented code with deployment support
Have an AI agent, RAG chatbot, MCP integration, or AI automation idea? Message me with your requirements before ordering, and I'll recommend the right technical approach.
Get to know Badar Younas
Badar Younas
Full Stack MERN Developer and AI Agent RAG Specialist
- FromPakistan
- Member sinceJun 2022
- Avg. response time1 hour
Languages
Urdu, English
"I'm a Full Stack MERN Developer and AI Agent RAG Specialist with expertise in building scalable, real-time web applications. I work with React, Node.js, Express, and MongoDB, along with Redux for state management and Socket.io for real-time features like chat and live updates. I also implement Redis caching and background job/queue workers (Bull, BullMQ) for high-performance, scalable systems. On the AI side, I build custom AI agents using RAG for smart, context-aware applications. Let's build something powerful for your business — reach out and let's discuss your project!".
My Portfolio
FAQ
Which AI models do you work with?
I work with OpenAI (GPT) and Google Gemini. Other LLMs can usually be added through their APIs depending on your project.
Can the AI agent use my private data safely?
Yes. Your data stays in your own vector database (ChromaDB, pgvector, or MongoDB Atlas). API keys are stored securely in environment variables and never exposed in the frontend.
What is MCP and do I need it?
MCP (Model Context Protocol) is a standard way for AI agents to use your tools, APIs, and data. You need it if you want the agent to take actions, not just answer questions.
What data can the chatbot learn from?
PDFs, Word docs, text files, website pages, databases, and APIs. Message me first if your data is large or in an unusual format.
Can you add this to my existing app?
Yes. I can integrate it into an existing MERN or REST-based project.
Will the agent give wrong answers?
RAG greatly reduces made-up answers because responses come from your data. I also tune retrieval and prompts so the agent says when it doesn't know instead of guessing.
Do I get the source code?
Yes, source code is included in all packages, plus setup instructions so you can run and maintain it yourself.
What do you need from me to start?
A short description of what the agent should do, the data it should use, and access to any APIs or tools it should connect to.
